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Layer: Building Footprint 2022 (ID: 240)

View In:   ArcGIS Online Map Viewer

Name: Building Footprint 2022

Display Field: County_Name

Type: Feature Layer

Geometry Type: esriGeometryPolygon

Description: This dataset provides a statewide collection of building footprint polygons for Mississippi. The core geometry was derived from BING Raster imagery by Microsoft. MARIS obtained the original dataset in JSON format and converted it to a WGS84 Geographic Coordinate System shapefile using MapShaper software. The dataset was subsequently reprojected into the NAD 1983 Mississippi Transverse Mercator (MSTM) coordinate system (Meters). The 2022 release contains approximately 1,507,496 building footprint polygons statewide.Key Components:Geometry: The dataset contains over 1.5 million structure polygons representing various building footprints. After quality control, the dataset was reduced to 1,502,581 structures by removing approximately 4,900 footprints located outside the state boundary and 15 polygons that were inaccurately positioned on roadways.Elevation Integration: Each polygon has been attributed with Z-values derived from statewide LIDAR datasets. This includes calculated values such as Ground Elevation (at the base of the structure).Parcel Linkage: Footprints are spatially joined to the Statewide Cadastral Framework, providing a link between physical structures and county tax assessor records (Parcels).Coordinate System: Projected in Mississippi State TM (MSTM).Data Lineage & Processing: The original Microsoft footprints were extracted using automated computer vision techniques and subsequently underwent a series of workflows. Users should be aware that while the data is highly comprehensive, accuracy is dependent on the date of the source imagery and LIDAR Dataset. MS Building Footprint polygons - 2022 ***** See source download and supplemental information for details on data creation by Microsoft. https://github.com/Microsoft/USBuildingFootprintsMicrosoft's explanation: “The gap areas contain image tiles taken with different cameras, which is causing the creation of artificial edges between neighboring tiles. These confuse our detection network, which hasn't learned to deal with them. We took a very conservative approach of skipping such tiles. I think we could add additional effort to properly deal with this problem.” LIDAR Data Source Year and Project Name:T2013_Lauderdale_LidarT2014_Central_Mississippi_LidarT2015_Coastal_Lidar___ContoursT2015_Southeast_Mississippi_Lidar_UTM15T2015_Southeast_Mississippi_Lidar_UTM16T2015_South_Central_Lidar_UTM15T2015_South_Central_Lidar_UTM16T2016_Southwest_LidarT2016_Camp_Shelby___ContoursT2016_Tishomingo_Lidar___ContoursT2018_Madison_Rankin_Lidar___ContoursT2018_Rankin_Simpson_Lidar___ContoursT2018_Tenn_Tom_Lidar___ContoursT2022_Delta_Lidar_UTM15T2022_Delta_Lidar_UTM16

Service Item Id: 0beebb3b96814ca5a7999a3b31227ef3

Copyright Text: Microsoft, BING, MARIS

Default Visibility: true

MaxRecordCount: 2000

MaxSelectionCount: 0

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 0.0

Max Scale: 0.0

Supports Advanced Queries: true

Supports Statistics: true

Can Scale Symbols: false

Use Standardized Queries: true

Supports ValidateSQL: true

Supports Calculate: true

Supports Datum Transformation: true

Extent:
Drawing Info: Feature Draw Order: Advanced Query Capabilities:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field:

Fields: Templates:
Capabilities: Query,Create,Update,Delete,Uploads,Editing

Sync Can Return Changes: false

Is Data Versioned: false

Supports Rollback On Failure: true

Supports ApplyEdits With Global Ids: false

Supports Query With Historic Moment: false

Supports Coordinates Quantization: true

Child Resources:

Supported Operations:   Query   Query Analytic   Apply Edits   Add Features   Update Features   Delete Features   Calculate   Append   Validate SQL   Generate Renderer   Return Updates   Iteminfo   Thumbnail   Metadata